Practical, Reproducible, and Statistically-Rigorous Workflows for Single-Nucleus Analysis of Childhood Cancer Data
When we talk about a cancer, we are talking about many cells that are growing and multiplying in ways that they should not. These cancer cells can also be supported by normal cells in the body that the cancer cells recruit. When we performed “genome-wide profiling” of a cancer in the past, we measured what was happening in the cancer cells, and usually some normal cells, all blended together and averaged. New technologies allow us to measure what’s happening in individual cells too. Unfortunately, measuring what’s happening at this resolution poses new challenges in how we analyze the data. Because these technologies are just starting to be used to study childhood cancers, we will design and implement workflows that account for these complexities, and we will make these workflows available to all researchers. This way, researchers studying childhood cancers can use the same or similar workflows to analyze data which will help scientists in the field compare and contrast across studies.
